WO2015146082A1 - Dispositif de détection de fuites, procédé de détection de fuites et support d'enregistrement contenant un programme - Google Patents

Dispositif de détection de fuites, procédé de détection de fuites et support d'enregistrement contenant un programme Download PDF

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WO2015146082A1
WO2015146082A1 PCT/JP2015/001519 JP2015001519W WO2015146082A1 WO 2015146082 A1 WO2015146082 A1 WO 2015146082A1 JP 2015001519 W JP2015001519 W JP 2015001519W WO 2015146082 A1 WO2015146082 A1 WO 2015146082A1
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value
leak
leakage
cross
correlation function
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PCT/JP2015/001519
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English (en)
Japanese (ja)
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友督 小野
宝珠山　治
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日本電気株式会社
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
    • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
    • F17D5/00—Protection or supervision of installations
    • F17D5/02—Preventing, monitoring, or locating loss
    • F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
    • G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
    • G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
    • G01M3/243—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations for pipes

Definitions

  • the present invention relates to a technique for detecting that a delivery target such as liquid or gas leaks from a delivery structure such as a pipe.
  • Patent Document 1 An example of a method for automating the specification of a leakage position is described in Patent Document 1.
  • sensors are installed at two points on both ends of a survey target section on a pipeline to measure the leak sound, and the leak point is determined based on the propagation time difference of the leak sound to the two sensors. Identify the location. Specifically, first, a cross-correlation function is calculated from leaked sound signals acquired by two sensors, and a propagation time difference of the leaked sound is calculated based on the calculated cross-correlation function value. Based on the calculated propagation time difference, the distance from the leakage point to the sensor installation position is obtained.
  • the pipe leakage detection method (correlation method) described in Patent Literature 1 is based on the point (peak) where the value of the cross-correlation function ⁇ ( ⁇ ) is the maximum value.
  • a propagation time difference Tm is calculated.
  • the accuracy of specifying the leakage position depends on how accurately the propagation time difference Tm is calculated.
  • Patent Document 1 There are many noisy environments, such as roads near busy roads and busy streets.
  • the piping leak detection method described in Patent Document 1 has a problem that it is difficult to accurately specify the leak position in an environment where such noise is generated.
  • the main object of the present invention is to provide a technique for solving the above-described problems.
  • a leak detection device that achieves the above-described object, Using signals representing the detection results of a plurality of sensors, the value of the cross-correlation function of these signals is calculated, the calculated value is equal to or greater than the first threshold value, and the time change of the calculated value at different measurement times is the first.
  • a leakage presence / absence determination means for determining that there is a leakage when the threshold is equal to or less than 2
  • a difference in propagation time of leaked sound is calculated based on a location where the value of the cross-correlation function is not less than the first threshold and the time change of the value of the cross-correlation function at different measurement times is not more than the second threshold.
  • leakage position calculation means for specifying the leakage position based on the propagation time difference.
  • a leakage detection method that achieves the above object is as follows. Using signals representing the detection results of multiple sensors, calculate the value of the cross-correlation function of those signals, It is determined that there is a leak when the value of the cross-correlation function is equal to or greater than a first threshold and the time change of the calculated value at different measurement times is equal to or less than a second threshold; A difference in propagation time of leaked sound is calculated based on a location where the value of the cross-correlation function is not less than the first threshold and the time change of the value of the cross-correlation function at different measurement times is not more than the second threshold. , A leak position is specified based on the propagation time difference.
  • a program that achieves the above object is as follows: On the computer, Using signals representing the detection results of multiple sensors, calculate the value of the cross-correlation function of those signals, It is determined that there is a leak when the value of the cross-correlation function is equal to or greater than a first threshold and the time change of the calculated value at different measurement times is equal to or less than a second threshold; A difference in propagation time of leaked sound is calculated based on a location where the value of the cross-correlation function is not less than the first threshold and the time change of the value of the cross-correlation function at different measurement times is not more than the second threshold. , The leakage position is specified based on the propagation time difference.
  • a further aspect of the present invention for achieving the above object is a computer-readable storage medium storing such a program.
  • FIG. It is a block diagram showing the structure of the leak detection apparatus which concerns on 4th embodiment of this invention. It is a block diagram showing the structure of the leak detection apparatus which concerns on 5th embodiment of this invention. It is a block diagram showing the structure of the leak detection apparatus which concerns on 7th embodiment of this invention. It is a figure explaining the structural example regarding embodiment of this invention. It is explanatory drawing which shows the example of the time change of the cross-correlation function (phi) ((tau)) calculated using the piping leak detection method of patent document 1.
  • FIG. It is a block diagram showing the structure of the leak detection apparatus which concerns on 6th embodiment of this invention. It is the figure which represented typically the time change of the cross correlation function (phi) ((tau)).
  • FIG. 6 is a diagram illustrating an identification boundary learned by an identification boundary learning unit 84. It is a block diagram showing the structure of the leak detection apparatus which concerns on 8th embodiment of this invention. And FIG. 11 is a block diagram illustrating an example of elements constituting a computer.
  • FIG. 10 is a diagram illustrating a configuration example relating to the embodiment of the present invention.
  • sensors 100 ⁇ / b> A and 100 ⁇ / b> B for measuring leakage sound are installed at two points on both ends of the survey target section L on the pipeline.
  • the position of the leak point (leakage location) 110 is specified based on the propagation time difference of the leaked sound to the sensor 100A and the sensor 100B.
  • the medium flowing through the pipe is gas, powder, liquid, or the like, and the present invention is not limited to a specific medium.
  • the leakage position is specified by utilizing the feature that leakage sound is generated steadily or substantially steadily and the correlation between a plurality of sensors installed in the pipe is large.
  • a leak detection device (not shown in FIG. 10) according to each of the following embodiments has a time ⁇ based on leaked sound signals measured by a plurality of sensors installed on a pipeline.
  • a cross-correlation function ⁇ ( ⁇ ), which is a function, is calculated from Equation 1.
  • x A (t) represents an input signal input from the sensor 100A at time t
  • x B (t) represents an input signal input from the sensor 100B at time t.
  • T represents the total measurement time.
  • FIG. 13 is a diagram schematically showing a time change of the cross-correlation function ⁇ ( ⁇ ).
  • FIG. 13 (a), 13 (b), and 13 (c) represent cross-correlation functions calculated from input signals at measurement times t1 to t2, t2 to t3, and t3 to t4, respectively.
  • a peak that always appears at the same time ⁇ and has a large value becomes a leaky sound.
  • FIGS. 13A, 13B, and 13C the value of “leakage sound” in FIGS. 13A, 13B, and 13C is large, and the amount that the value fluctuates at different measurement times is small. It is.
  • other sudden peaks are regarded as peaks caused by noise.
  • FIG. 1 is a block diagram showing a configuration of a leak detection apparatus according to the first embodiment of the present invention.
  • the leak detection apparatus A1 according to the first embodiment of the present invention includes a signal input unit 10, a time division unit 11, a cross-correlation function calculation unit 12, an average / variance calculation unit 13, and a leak presence / absence determination unit 15. , A propagation time difference calculation unit 16 and a leakage position calculation unit 17 are provided.
  • the signal input unit 10 inputs time-synchronized signals obtained by sensors installed at two points across the inspection target section. The longer the input signal measurement time, the higher the accuracy.
  • the measurement time of the input signal may be 24 hours, for example.
  • the time division unit 11 outputs a signal obtained by dividing the total measurement time of the two input signals into fixed time intervals (periods) T, respectively.
  • the cross-correlation function calculating unit 12 calculates a cross-correlation function for each signal obtained by the time dividing unit 11 from two input signals at each divided measurement time.
  • the cross-correlation function in a certain divided measurement time (t n to (t n + T)) ⁇ n ( ⁇ ) is given as a function of time ⁇ as shown in Equation 2.
  • the number 2-2 normalized by may be used as the cross-correlation function ⁇ n ( ⁇ ). [Equation 2-2]
  • the average / dispersion calculation unit 13 calculates a function M ( ⁇ ) that gives an average value of ⁇ n ( ⁇ ) for each ⁇ and a function V ( ⁇ ) that gives a dispersion value by Equations 3 and 4, respectively.
  • the function M ( ⁇ ) is an average value divided through each of the different measurement times.
  • the function V ( ⁇ ) is a dispersion value divided through different measurement times.
  • the variance value refers to a value that represents the degree to which the sample values are scattered from the average value. The variance value is obtained by, for example, averaging the square of the difference between the value of each sample and the average value. [Equation 3]
  • N is the number of measurement signals divided by the time division unit 11.
  • the thresholds M th and V th are determined based on the actually acquired leakage sound. If there is no ⁇ ′ that satisfies both of the two conditions of Equation 5, the leakage presence / absence determination unit 15 determines that there is no leakage, and the process ends.
  • FIG. 2 is a conceptual diagram for explaining the determination method in the leakage presence / absence determination unit 15 in the case of leakage sound and noise.
  • 2A, 2B, and 2C show the cross-correlation function ⁇ n ( ⁇ ) in the case of leakage sound and noise.
  • 2 (A), FIG. 2 (B), and FIG. 2 (C) are plots of the average value and dispersion value of ⁇ n ( ⁇ ) for each ⁇ in FIG. D), (E) in FIG. 2, and (F) in FIG. In the case of (A) in FIG. 2 and (D) in FIG.
  • the leakage presence / absence determining unit 15 Is regarded as a peak of ⁇ n ( ⁇ ) due to leaked sound, and it is determined that there is a leak.
  • the leakage presence / absence determination unit 15 determines noise (not leakage).
  • the leakage presence / absence determination unit 15 determines noise (not leakage).
  • Propagation time difference calculating portion 16 calculates the 2 satisfies ⁇ 'number 5 as the propagation time difference T m of a leakage sound. When there are a plurality of ⁇ satisfying the two conditions of Equation 5, it is considered that there are a plurality of leakage points, and the propagation time difference Tm is calculated for each.
  • L a (L ⁇ T m C) / 2
  • L b L ⁇ L a
  • C represents the leakage sound propagation speed.
  • FIG. 14 is a flowchart for explaining the operation of the leak detection apparatus A1 in the first embodiment.
  • operation movement of the leak detection apparatus A1 in 1st embodiment is demonstrated.
  • the signal input unit 10 inputs a signal representing a detection result obtained from two sensors synchronized in time (step S1).
  • the time division unit 11 outputs a signal obtained by dividing the total measurement time of the two obtained input signals into fixed time intervals (step S2).
  • the cross-correlation function calculation unit 12 calculates a cross-correlation function of two input signals at each time ⁇ for each of the divided signals (step S3).
  • the average / variance calculation unit 13 calculates the average value and the variance value of the cross-correlation function for each time ⁇ (step S4).
  • the leakage presence / absence determination unit 15 compares the average value and the variance value of the cross-correlation function with a predetermined threshold value (step S5). Then, the leakage presence / absence determination unit 15 determines that there is leakage when there is one or more time ⁇ in which the average value is greater than or equal to the threshold value and the variance value is less than or equal to the threshold value (YES in step S5) (step S6). In other cases (NO in step S5), it is determined that there is no leakage (step S7). If it is determined that the leakage is present, the propagation time difference calculating portion 16, by regarding the propagation time difference of the leakage sounds time tau, calculates the propagation time difference T m (step S8). The leakage position calculation unit 17 calculates the distance from the leakage point to each sensor based on Tm (step S9).
  • the leak detection device A1 uses the continuity of leaked sound and the correlation between multiple sensors to increase the value of the cross-correlation function and change with time. If it is small, the position is identified as a peak due to leaked sound. Specifically, the leakage detection apparatus A1 determines whether the cross-correlation function value is large and the time change is small by determining whether the average value of the cross-correlation function is equal to or greater than the threshold value and the variance value is equal to or less than the threshold value. Determine. For this reason, the leak detection apparatus A1 has an effect that the presence / absence of the leak and the leak position can be specified even in an environment where noise is generated. In particular, even when there is noise that overlaps the leaked sound and the frequency band, such as a running sound of an automobile, the leak detection device A1 can accurately identify the presence / absence of the leak and the leak position.
  • FIG. 3 is a block diagram showing the configuration of the leak detection apparatus according to the second embodiment of the present invention.
  • the leak detection device A2 according to the second embodiment of the present invention is replaced with the average / dispersion calculation unit 13, the leak presence / absence determination unit 15, and the propagation time difference calculation unit 16 in the leak detection device A1 of the first embodiment.
  • the mode value calculation unit 23, the leakage presence / absence determination unit 25, and the propagation time difference calculation unit 26 are included.
  • the mode value calculation unit 23 is a cross-correlation function ⁇ n ( ⁇ ) (0 ⁇ n ⁇ N) in the divided measurement times (t n to (t n + T)) obtained by the cross-correlation function calculation unit 12.
  • Equation 7 The number of times (frequency) C ( ⁇ , i) where ⁇ n ( ⁇ ) satisfies the inequality of Equation 7 is counted for each ⁇ and each i. That is, the mode value calculation unit 23 converts the value of ⁇ n ( ⁇ ) to the section values (b 0 to b 1 ,..., B i to b i + 1 ,..., B M ⁇ 1 to b for each predetermined section width S. M ). Then, the mode value calculation unit 23 counts the number of times (appearance frequency) corresponding to the value of ⁇ n ( ⁇ ) for each section value. Thereafter, as shown in Equation 8, the mode value calculation unit 23 calculates the maximum value (mode) C m ( ⁇ ) of C ( ⁇ , i) and the cross-correlation function ⁇ ( ⁇ ) is calculated. [Equation 7]
  • the minimum value b 0 of b i is the minimum value of ⁇ n ( ⁇ )
  • the maximum value b M is the maximum value of ⁇ n ( ⁇ ).
  • An example of the frequency distribution (histogram) of the cross-correlation function obtained by the mode value calculation unit 23 is shown in FIG.
  • the vertical axis is a value obtained by normalizing the frequency C ( ⁇ , i) by the section width S.
  • FIG. [Equation 9] C m ( ⁇ ′) / S> C th ⁇ ( ⁇ ′)> ⁇ th
  • the threshold values C th and ⁇ th indicated by dotted lines in FIG. 4 are determined from the actually acquired leaked sound. As shown in (B) of FIG. 4 and (C) of FIG.
  • the propagation time difference calculation unit 26 calculates ⁇ ′ when the condition of Equation 9 is satisfied as the propagation time difference T m caused by the leaked sound.
  • FIG. 15 is a flowchart for explaining the operation of the leak detection apparatus A2 in the second embodiment.
  • the operation of the leakage detection apparatus A2 including the mode value calculation unit 23, the leakage presence / absence determination unit 25, the propagation time difference calculation unit 26, and the leakage position calculation unit 17 will be described with reference to the flowchart of FIG. .
  • the same number is provided and description is abbreviate
  • the cross-correlation function calculation unit 12 calculates a cross-correlation function between two input signals at each time for the divided signals (step S3).
  • the mode value calculation unit 23 calculates the frequency of the cross-correlation function at each time ⁇ (step S14), and calculates the maximum value (mode value) of the frequency and the cross-correlation function when the mode value is taken ( Step S15).
  • the leakage presence / absence determination unit 25 compares the mode value and the cross-correlation function when taking the mode value with a threshold value (step S16). Then, the leakage presence / absence determination unit 25 determines that there is leakage when there is a time ⁇ in which both exceed the threshold (YES in step S16), and outputs a determination result (step S17), otherwise (step S17). If NO in S16, it is determined that there is no leakage, and the process ends (step S18).
  • the propagation time difference calculation unit 26 calculates the time ⁇ when the cross-correlation function when taking the mode value and the mode value exceeds the threshold as the propagation time difference T m (step S19).
  • the leakage position calculating section 17 calculates the leakage position from the propagation time difference T m (step S20).
  • the leak detection device A2 constantly leaks sound but does not temporarily generate noise while measuring a long-time input signal.
  • the feature that there is a time zone is used. Therefore, the leak detection device A2 can determine whether there is a leak and specify the leak position even in an environment where noise frequently occurs, such as a road with a lot of traffic.
  • the sensor input signal is divided into fixed time intervals as in the first embodiment or the second embodiment.
  • a time interval in which the levels of the input signals of a plurality of sensors are low is extracted, and each interval is divided into fixed time intervals.
  • the leak detection devices A3 and A3 ′ according to the third embodiment of the present invention have leak detection devices A1 and A1 of the first embodiment and the second embodiment, respectively, as shown in FIGS. 6A and 6B.
  • a signal level calculation unit 30 and an evaluation interval calculation unit 31 are provided after the signal input unit 10 in A2.
  • the leak detection devices A3 and A3 ′ according to the third embodiment of the present invention determine whether there is a leak in a noise environment and specify the leak position. This has the effect of increasing the accuracy.
  • the leak detection device A4 according to the fourth embodiment of the present invention has a signal input unit 40 instead of the signal input unit 10 in the leak detection device A2 of the second embodiment.
  • the signal input unit 40 does not input a signal continuously for 24 hours, but measures one hour every three hours, for example, to measure for a certain period at a certain time interval. To do.
  • the leak detection device A4 according to the fourth embodiment of the present invention can efficiently acquire various data of day and night even when the amount of data and power that can be processed are limited.
  • the leak detection apparatus A4 which concerns on 4th embodiment of this invention has the effect that a leak presence determination and leak position specification can be performed without reducing accuracy.
  • the value of the cross-correlation function is particularly high.
  • the average value is calculated from only the remaining value without using the value at that time as the abnormal value.
  • N 100 and the cross correlation function values are arranged in descending order, the remaining 80 other than the values of the top 10 and the bottom 10
  • the average value M ( ⁇ ) is given by Equation 10.
  • Equation 11 median ⁇ ( ⁇ ) may be calculated from Equation 11 instead of the average value.
  • the leak detection device A5 uses an average / variance instead of the average / variance calculation unit 13 in the leak detection device A1 of the first embodiment.
  • a calculation unit 53 is included.
  • the leakage presence / absence determination unit 15 of the first embodiment determines the presence / absence of leakage by comparing the average value and the variance value of the cross-correlation function with a threshold value.
  • an identification boundary on the average / dispersion graph is set. Learning is performed, and the presence or absence of leakage is determined depending on which side the evaluation target signal is located with respect to the identification boundary.
  • the identification boundary is a boundary line that defines each region when there is leakage and when there is no leakage. That is, the identification boundary is a set of combinations of average values and variance values (points on the average / variance graph) that serve as a boundary for determining whether there is leakage.
  • the leak detection device A6 is a leak sound / noise signal input unit instead of the leak presence / absence determination unit 15 in the leak detection device A1 of the first embodiment.
  • 80 a time division unit 81, a cross-correlation function calculation unit 82, an average / variance calculation unit 83, an identification boundary learning unit 84, and a leakage presence / absence determination unit 95.
  • the leaked sound / noise signal input unit 80 inputs a plurality of leaked sounds and noises different from the evaluation target signal input by the signal input unit 10. Leakage sound is measured by installing sensors at two points on the pipeline across the leak point. Noise is measured by sensors installed at two points on the pipeline where there is no leakage in the vicinity.
  • the time division unit 81 and the cross-correlation function calculation unit 82 are respectively connected to the time division unit 11 and the cross-correlation function calculation unit 12 of the first embodiment with respect to the signal input from the leaked sound / noise signal input unit 80. A similar operation is performed.
  • the average / dispersion calculation unit 83 calculates a function M ( ⁇ ) that gives an average value of a cross-correlation function and a function V ( ⁇ ) that gives a dispersion value from Equations 3 and 4, respectively, for each leaked sound and noise.
  • the discrimination boundary learning unit 84 calculates a support vector machine (SVM), a neural network, and a k-neighbor discriminator from values of M ( ⁇ ) and V ( ⁇ ) of the leaked sound and noise obtained by the average / variance calculation unit 83.
  • SVM support vector machine
  • a discriminating boundary on a two-dimensional space is learned using a discriminator such as.
  • the leakage presence / absence determination unit 95 determines that there is leakage when the average value and the variance value of the evaluation target signal calculated by the average / variance calculation unit 13 are on the leakage sound side with respect to the identification boundary, and the noise side It is determined that there is no leakage.
  • FIG. 16 is a conceptual diagram showing the identification boundary learned by the identification boundary learning unit 84.
  • the horizontal axis in FIG. 16 is the average value, and the vertical axis is the variance value.
  • the leaked sound and noise prepared in advance are indicated by black circles and white circles, respectively.
  • the dotted line is the identification boundary learned from leaked sound and noise. If the evaluation signal is in the shaded area, it is determined that there is a leak, and if it is in any other area, it is determined that there is no leak.
  • the leak detection device A6 according to the sixth embodiment of the present invention can perform determination with higher accuracy in addition to the effects of the first embodiment.
  • the leakage presence / absence determination unit 25 of the second embodiment determines the presence / absence of leakage by comparing the mode value and the cross-correlation function with a threshold value.
  • an identification boundary on the histogram of the cross-correlation function based on a plurality of leaked sound signals (leakage sound information) and noise signals (noise information) acquired in advance. And determining whether or not there is a leak depending on which side the mode value of the signal to be evaluated is located with respect to the identification boundary.
  • the identification boundary is a boundary line that defines each region when there is leakage and when there is no leakage. That is, the identification boundary is a set of combinations of the interval value and the appearance frequency (points on the histogram of the cross-correlation function) that serve as a determination boundary for the presence or absence of leakage.
  • the leak detection device A7 is a leak sound / noise signal input unit instead of the leak presence / absence determination unit 25 in the leak detection device A2 of the second embodiment.
  • 80 a time division unit 81, a cross-correlation function calculation unit 82, a mode value calculation unit 63, an identification boundary learning unit 64, and a leakage presence / absence determination unit 85.
  • the leaked sound / noise signal input unit 80, the time division unit 81, and the cross-correlation function calculation unit 82 respectively calculate a cross-correlation function for a plurality of leaked sounds and noises. calculate.
  • the mode value calculation unit 63 counts the number of times (frequency) C ( ⁇ , i) that the cross-correlation function ⁇ n ( ⁇ ) satisfies the inequality of Equation 7 for each ⁇ and each i, and then, as shown in Equation 12. , C ( ⁇ , i) maximum value (mode) C m ′ is calculated. [Equation 12]
  • the discriminating boundary learning unit 64 uses the mode C m ′ of the noise and leaked sound obtained by the mode calculation unit 63 and the value of the cross-correlation function ⁇ n ( ⁇ ′, i ′) at that time. Using a classifier such as a support vector machine, a neural network, or a k-neighbor classifier, a classification boundary on a two-dimensional space (cross correlation function histogram) is learned.
  • the leakage presence / absence determination unit 85 determines that there is leakage when the mode value of the evaluation target signal calculated by the mode value calculation unit 23 is on the leakage sound side with respect to the identification boundary, and is on the noise side. It is determined that there is no leakage.
  • FIG. 5 is a conceptual diagram showing the histogram of the cross-correlation function calculated from the evaluation target signal and the identification boundary learned in advance.
  • the horizontal axis in FIG. 5 is the value of the cross-correlation function ⁇ ( ⁇ ), and the vertical axis is the value obtained by normalizing the frequency C ( ⁇ , i) by the section width S.
  • the histogram of the signal to be evaluated since the histogram of the signal to be evaluated enters the hatched area surrounded by the identification boundary, it is determined that there is a leak.
  • the leak detection device A7 according to the seventh embodiment of the present invention can perform the determination with higher accuracy in addition to the effects of the second embodiment.
  • FIG. 17 is a block diagram showing the configuration of the leak detection apparatus according to the eighth embodiment of the present invention.
  • the leak detection device A8 according to the eighth embodiment of the present invention includes a leak presence / absence determination unit 15 and a leak position calculation unit 17.
  • the leakage presence / absence determination unit 15 determines that there is leakage when the value of the cross-correlation function between input signals input from a plurality of sensors is equal to or greater than a threshold value and the time change is equal to or less than the threshold value.
  • the leakage position calculation unit 17 calculates the propagation time difference of the leaked sound based on the location where the value of the cross-correlation function is equal to or greater than the threshold value and the time change is equal to or less than the threshold value, and specifies the leakage position based on the propagation time difference.
  • the leak detection device A8 has a large value of the cross-correlation function and a change over time by utilizing the steadiness of the leaked sound and the correlation between the plurality of sensors. If small, it is determined that there is a leak. Then, the leak detection device A8 calculates the propagation time difference of the leaked sound based on the location where the value of the cross-correlation function is large and the time change is small, and specifies the leak position based on the propagation time difference. For this reason, the leak detection apparatus A8 has an effect that the presence / absence of the leak and the leak position can be specified even in an environment where noise is generated.
  • FIG. 18 is a block diagram showing an example of elements constituting the computer.
  • a computer 900 in FIG. 18 includes a CPU (Central Processing Unit) 910, a RAM (Random Access Memory) 920, a ROM (Read Only Memory) 930, a hard disk drive 940, and a communication interface 950.
  • CPU Central Processing Unit
  • RAM Random Access Memory
  • ROM Read Only Memory
  • the components of the leak detection devices A1, A2, A3, A3 ′, A4, A5, A6, A7, and A8 described above are realized by executing a program (software program, computer program) in the CPU 910 of the computer 900. Also good. Specifically, the time division units 11 and 81 that are the components described in FIGS.
  • the mode value calculation units 23 and 63, the signal level calculation unit 30, the evaluation section extraction unit 31, and the identification boundary learning units 64 and 84 read the program read by the CPU 910 from the ROM 930 or the hard disk drive 940. For example, it may be realized by execution by the CPU 910 as in the procedures of the flowcharts shown in FIGS.
  • the present invention described by using the above-described embodiment as an example can be applied to a computer-readable storage medium (for example, hard disk drive 940 or the like) that stores a code representing the computer program or a code representing the computer program. It can be understood that it is constituted by a removable magnetic disk medium, optical disk medium, memory card, etc. (not shown).
  • the time division units 11, 81, the cross-correlation function calculation units 12, 82, the average / variance calculation units 13, 53, 83, the leakage presence / absence determination units 15, 25, 85, 95, and the propagation time difference calculation unit 16 , 26, leakage position calculation unit 17, mode value calculation units 23 and 63, signal level calculation unit 30, evaluation interval extraction unit 31, and identification boundary learning units 64 and 84 are realized by dedicated hardware. May be. Further, the leakage detection devices A1, A2, A3, A3 ′, A4, A5, A6, A7, and A8 may be dedicated hardware including these components.
  • a leakage presence / absence determination means for determining that there is a leakage when the threshold is equal to or less than 2
  • a difference in propagation time of leaked sound is calculated based on a location where the value of the cross-correlation function is not less than the first threshold and the time change of the value of the cross-correlation function at different measurement times is not more than the second threshold.
  • a leak detection device comprising: a leak position calculation means for specifying a leak position based on the propagation time difference.
  • the leak presence / absence determining means has a leak when a section value of the cross-correlation function assigned for each predetermined section width is equal to or greater than a fifth threshold and the frequency of appearance of the section value is equal to or greater than a sixth threshold.
  • an identification boundary learning means for learning an identification boundary that is a set of combinations of the average value and the variance value, which is a boundary for determining whether there is leakage
  • the leakage detection apparatus according to appendix 2 or 4, wherein the leakage presence / absence determination means determines whether there is leakage based on the identification boundary.
  • An identification boundary learning unit that learns an identification boundary that is a set of combinations of the section value and the appearance frequency, which is a boundary for determining whether there is leakage, based on a plurality of leaked sound information and noise information acquired in advance.
  • the leakage detection device according to supplementary note 3, wherein the leakage presence / absence determination means determines whether there is leakage based on the identification boundary.
  • the discrimination boundary learning means learns the discrimination boundary using a discriminator that is one of a support vector machine, a neural network, and a k-neighbor discriminator,
  • the leakage presence / absence determining means determines that there is leakage when the mode value of the input signal to be evaluated is on the leakage sound side with respect to the identification boundary, and determines that there is no leakage when on the noise side. 5.
  • the leak detection device according to 5 or 6.
  • a cross-correlation function calculating unit that extracts a section whose level is equal to or less than a threshold value from the input signal, divides the extracted section into fixed time intervals, and calculates a cross-correlation function between the divided input signals;
  • the leak detection device according to any one of appendices 1 to 7.
  • Appendix 11 The leak detection method according to appendix 10, wherein it is determined that there is a leak when an average value over different measurement times of the cross-correlation function value is equal to or greater than a third threshold value and a variance value is equal to or less than a fourth threshold value.
  • Appendix 14 Based on a plurality of leaked sound information and noise information acquired in advance, learn an identification boundary that is a set of a combination of the average value and the variance value, which is a boundary for determining whether there is leakage, 14.
  • appendix 20 On the computer, The program according to appendix 19, which executes a process of determining that there is a leak when an average value of the cross-correlation function values during a predetermined period is equal to or greater than a third threshold value and a variance value is equal to or less than a fourth threshold value.
  • Appendix 22 On the computer, 21.
  • Appendix 23 On the computer, Based on a plurality of leaked sound information and noise information acquired in advance, a process for learning an identification boundary that is a set of combinations of the average value and the variance value, which is a boundary for determining whether there is leakage, The program according to appendix 20 or 22, which executes a process of determining the presence or absence of leakage based on the identification boundary.
  • Appendix 25 On the computer, Learning the discrimination boundary using a discriminator that is one of a support vector machine, a neural network, and a k-neighbor discriminator; Appendix 23 or 23 for executing a process of determining that there is a leak when the mode value of the input signal to be evaluated is on the leaky sound side with respect to the identification boundary and determining that there is no leak when on the noise side 24.
  • the program according to 24 The program according to 24.
  • Appendix 26 On the computer, A process of extracting a section whose level is equal to or lower than a threshold value from the input signal; A process of dividing the extracted section into a certain time interval; The program according to any one of appendices 19 to 25, wherein the program executes a process of calculating a cross-correlation function between the divided input signals.

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  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Examining Or Testing Airtightness (AREA)

Abstract

La présente invention concerne la détection de fuites dans des tuyaux, avec un haut degré de précision, même dans des environnements bruyants. Le dispositif de détection de fuites de l'invention comprend les éléments suivants : une unité de détermination de présence de fuite qui utilise des signaux représentant les résultats de détection provenant d'une pluralité de capteurs pour calculer la valeur d'une fonction de corrélation croisée pour lesdits signaux et, si la valeur calculée est supérieure ou égale à un premier seuil et que le changement dans le temps présenté par une valeur calculée à partir de mesures à un moment différent est inférieur ou égal à un second seuil, détermine qu'une fuite est présente ; et une unité de calcul d'emplacement de fuite qui calcule des différences de temps de propagation du son des fuites sur la base de zones pour lesquelles la valeur de la fonction de corrélation croisée susmentionnée est supérieure ou égale au premier seuil susmentionné et le changement dans le temps présenté par la valeur de ladite fonction de corrélation croisée à partir de mesures à un moment différent est inférieur à ou égal au second seuil susmentionné et identifie l'emplacement de la fuite sur la base desdites différences de temps de propagation.
PCT/JP2015/001519 2014-03-26 2015-03-18 Dispositif de détection de fuites, procédé de détection de fuites et support d'enregistrement contenant un programme WO2015146082A1 (fr)

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